1. Field of the Invention
The present invention relates to systems and methods useful for collecting consumer data, and more particularly to systems and methods for collecting data representative of consumer buying habits over networks.
2. Brief Description of the Related Art
Consumer decision making has been a focus for many years. Companies that are attempting to meet a particular need in the marketplace, or that are attempting to find out how their products or services are being received by the consumer, will often conduct market research to attempt to quantify attributes or characteristics of a particular consumer segment. If performed well, the data extracted from this research can inform companies about how their products or services are perceived and bought by purchasers or potential purchasers in the marketplace, and how the companies' products or services can be changed to achieve the companies' business goals.
Traditionally, there have been numerous other general protocols for performing consumer-oriented market research. A pool of consumers is first selected, and then each individual person in the pool is asked to provide information about themselves, their purchasing and perceptions of products or services, and/or their buying decisions, among other things. Many different ways have been proposed in the past for eliciting and recording this information from the individual consumer. For example, for television viewing habits, an electronic device has been attached to the television consumer's television set which is capable of recording which specific channels were tuned in, at what time, and for how long.
Perhaps the most simple prior protocol for collecting such data has been to simply ask the consumers to write down data about their buying habits, or to survey a random selection of people either personally, over the telephone, or by using a mailed survey.
Other prior data collection protocols concerned collecting data about consumers' buying habits. For example, one prior protocol involved the consumer being given an electronic device which includes a Universal Product Code (UPC) (bar code) scanner. The consumer was requested to scan in every item that the consumer bought over a period of time, and to enter other information regarding the purchase (e.g., at what retailer the purchase was made). The consumer then connected the device to an intelligent modem. The device would dial up and connect to a host computer, and upload the scanned information to the host computer to be collected and processed.
Another data collection protocol, commonly used by consumer package goods retailers, is to ask the consumer to show an ID card at checkout. The check-out clerk then inputs the ID number and scans the items bought for both pricing and gathering data about the consumer's grocery buying habits. The retailer then can use this data about the individual consumer to make consumer-specific promotional offers. Data from many consumers can be merged together and sold to another party for marketing intelligence, or the like.
The above prior data collection protocols suffer from numerous deficiencies, in the traditional and modern marketplace. In particular, it has proven difficult to adapt these protocols to internet-based electronic commerce. Compared to the relative ease by which consumers are able to receive information and make decisions based on information from the internet, prior data collection protocols are cumbersome, do not interface well (if at all) with computer-based consumer activity, and are therefore not well suited for collecting data about internet-based activity.
Some internet-activity monitoring has been proposed. For example, a server-side consumer data collection strategy has been proposed in which an individual internet content provider (“website”) monitors and collects data about each consumer who has requested data from (“visited”) the website, and then compiles this data about all the consumers who have visited that website. This data could include purchases; the specific type or subject of information requested from the site; and the like. Furthermore, the website also collects data about how frequently particular files or groups of files (“webpage”) have been visited (commonly referred to as “click through hits”), that is, a measure of the popularity of a particular website or webpage. This is one form of server-side data collection.
Another form of server-side consumer data collection requires a consumer to visit a particular website specifically for the purpose of providing information about that individual's buying habits, in return for which the website compensates the individual, with incentives such as money, gifts, credits, or the like.
Data collection directly from an internet consumer's computer has also been proposed, i.e., client-side data collection. Such systems commonly involve installing a large and cumbersome software application onto the consumer's computer, which operates at the same time as internet browser application software. The software then collects data about the consumer's internet usage, i.e., which websites the consumer has visited. The data is then uploaded to a data collecting computer on the internet.
These prior internet activity protocols and systems have numerous disadvantages and deficiencies. While both the above server-side and client-side data collection systems are capable of collecting data about a particular consumer, they both suffer from certain failings. For example, prior server-side systems only are capable of collecting data about a consumer's activities at a single website, as it is that website itself that is collecting the data. If the consumer clicks-through to another site, e.g., an advertiser's site, the consumer and their information is thereafter lost. Furthermore, it is difficult for server-side systems to collect data about the consumer, such as age, income level, marital status, and other demographic, economic, and personal information, which would allow the data to be compared with consumer databases from other source. Many consumers are simply unwilling to give this sensitive information to an otherwise unknown party without some incentive being provided. Thus, in order to get statistically significant market data, the website would have to be visited by an enormous number of internet consumers.
Prior client-side systems likewise suffer from different, but nevertheless severe, deficiencies. Because prior client-side systems require the use of an additional application to gather data, which application runs on the consumer's computer at the same time as the consumer's internet browser, the computer is slowed down by the added impact on its system's resources. Thus, the consumer notices a delay in the operation of her computer, which is not acceptable to many consumers. Uploading collected data also takes away from internet bandwidth, which also is unacceptable to many consumers. In order to interpret the raw data from the internet that this specialized software shares with the internet browser, it is necessary for the client-side software to include data or instructions which allows the software to interpret the data from specific websites. When these specific websites change the format of the data they send to internet consumers, the specialized software must be updated so that the new data format(s) can be properly interpreted. Thus, when a website changes the layout or content of a webpage that the client-side software is supposed to monitor, the client-side software on each participating internet consumer's computer must be updated. As will be immediately appreciated, this can be a large, cumbersome, and expensive undertaking. Because the software installed on the client-side computer is complicated, it is also not unusual for technical problems to occur. This necessitates the maintenance of a large customer service center to help answer consumer's questions and solve their problems. This can also be a very expensive undertaking.
Furthermore, such client-side systems require a very large sample size of internet users in order to have statistically significant data, because the number of internet users who visit a website is much greater than the number of internet consumers who perform some internet activity, such as making a purchase, listening to a sound or song, watching a video, or requesting a specific type of information. Because of the expensive features of prior client-side systems, the costs per panelist to maintain these measurement systems are extraordinarily high.